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Related papers: The shape of incomplete preferences

200 papers

This paper studies axioms for nonmonotonic consequences from a semantics-based point of view, focusing on a class of mathematical structures for reasoning about partial information without a predefined syntax/logic. This structure is called…

Logic in Computer Science · Computer Science 2007-05-23 Guo-Qiang Zhang

In this work we generalize standard Decision Theory by assuming that two outcomes can also be incomparable. Two motivating scenarios show how incomparability may be helpful to represent those situations where, due to lack of information,…

Computer Science and Game Theory · Computer Science 2014-04-04 Piero A. Bonatti , Marco Faella , Luigi Sauro

We present an extension-based approach for computing and verifying preferences in an abstract argumentation system. Although numerous argumentation semantics have been developed previously for identifying acceptable sets of arguments from…

Artificial Intelligence · Computer Science 2024-03-27 Quratul-ain Mahesar , Nir Oren , Wamberto W. Vasconcelos

Model selection and assessment with incomplete data pose challenges in addition to the ones encountered with complete data. There are two main reasons for this. First, many models describe characteristics of the complete data, in spite of…

Methodology · Statistics 2008-08-28 Geert Verbeke , Geert Molenberghs , Caroline Beunckens

Current work in planning with preferences assume that the user's preference models are completely specified and aim to search for a single solution plan. In many real-world planning scenarios, however, the user probably cannot provide any…

Artificial Intelligence · Computer Science 2015-03-17 Tuan Nguyen , Minh Do , Alfonso Gerevini , Ivan Serina , Biplav Srivastava , Subbarao Kambhampati

We introduce a new approach to modeling uncertainty based on plausibility measures. This approach is easily seen to generalize other approaches to modeling uncertainty, such as probability measures, belief functions, and possibility…

Artificial Intelligence · Computer Science 2016-08-31 Nir Friedman , Joseph Y. Halpern

We introduce a novel notion of probability within quantum history theories and give a Gleasonesque proof for these assignments. This involves introducing a tentative novel axiom of probability. We also discuss how we are to interpret these…

Quantum Physics · Physics 2015-06-26 Thomas Marlow

Various structured argumentation frameworks utilize preferences as part of their standard inference procedure to enable reasoning with preferences. In this paper, we consider an inverse of the standard reasoning problem, seeking to identify…

Artificial Intelligence · Computer Science 2020-05-13 Quratul-ain Mahesar , Nir Oren , Wamberto W. Vasconcelos

We introduce a new class of graphical representations, expected utility networks (EUNs), and discuss some of its properties and potential applications to artificial intelligence and economic theory. In EUNs not only probabilities, but also…

Computer Science and Game Theory · Computer Science 2024-01-18 Pierfrancesco La Mura , Yoav Shoham

This paper introduces a space of variable lotteries and proves a constructive version of the expected utility theorem. The word ``constructive'' is used here in two senses. First, as in constructive mathematics, the logic underlying proofs…

Theoretical Economics · Economics 2024-02-28 Kislaya Prasad

We perform a stability analysis for the utility maximization problem in a general semimartingale model where both liquid and illiquid assets (random endowments) are present. Small misspecifications of preferences (as modeled via expected…

Portfolio Management · Quantitative Finance 2010-03-17 Constantinos Kardaras , Gordan Zitkovic

We consider the task of forecasting an infinite sequence of future observations based on some number of past observations, where the probability measure generating the observations is "suspected" to satisfy one or more of a set of…

Machine Learning · Computer Science 2019-05-17 Vanessa Kosoy

As the information available to lay users through autonomous data sources continues to increase, mediators become important to ensure that the wealth of information available is tapped effectively. A key challenge that these information…

Databases · Computer Science 2012-08-29 Rohit Raghunathan , Sushovan De , Subbarao Kambhampati

Several Artificial Intelligence schemes for reasoning under uncertainty explore either explicitly or implicitly asymmetries among probabilities of various states of their uncertain domain models. Even though the correct working of these…

Artificial Intelligence · Computer Science 2013-02-28 Marek J. Druzdzel

The weak axiom of revealed preference (WARP) ensures that the revealed preference (i) is a preference relation (i.e., it is complete and transitive) and (ii) rationalizes the choices. However, when WARP fails, either one of these two…

Theoretical Economics · Economics 2024-01-15 Pablo Schenone

Let $\succsim$ be a binary relation on the set of simple lotteries over a countable outcome set $Z$. We provide necessary and sufficient conditions on $\succsim$ to guarantee the existence of a set $U$ of von Neumann--Morgenstern utility…

Classical Analysis and ODEs · Mathematics 2024-01-17 Paolo Leonetti

A flexible representation of uncertainty that remains within the standard framework of probabilistic measure theory is presented along with a study of its properties. This representation relies on a specific type of outer measure that is…

Information Theory · Computer Science 2016-11-10 Jeremie Houssineau , Daniel E. Clark

Physicists have, hitherto, mostly adopted a frequentist conception of probability, according to which probability statements apply only to ensembles. It is argued that we should, instead, adopt an epistemic, or Bayesian conception, in which…

Quantum Physics · Physics 2009-11-10 D. M. Appleby

Desirability can be understood as an extension of Anscombe and Aumann's Bayesian decision theory to sets of expected utilities. At the core of desirability lies an assumption of linearity of the scale in which rewards are measured. It is a…

Artificial Intelligence · Computer Science 2022-11-21 Enrique Miranda , Marco Zaffalon

Inferring a decision maker's utility function typically involves an elicitation phase where the decision maker responds to a series of elicitation queries, followed by an estimation phase where the state-of-the-art is to either fit the…

Applications · Statistics 2018-07-31 Mengyang Gu , Debarun Bhattacharjya , Dharmashankar Subramanian